Klostermann Melina, Zarnack Kathi
Faculty of Biosciences, Buchmann Institute for Molecular Life Sciences & Institute of Molecular Biosciences, Goethe University Frankfurt, Frankfurt am Main 60438, Germany.
Bioinform Adv. 2024 Jun 26;4(1):vbae084. doi: 10.1093/bioadv/vbae084. eCollection 2024.
A vast variety of biological questions connected to RNA-binding proteins can be tackled with UV crosslinking and immunoprecipitation (CLIP) experiments. However, the processing and analysis of CLIP data are rather complex. Moreover, different types of CLIP experiments like iCLIP or eCLIP are often processed in different ways, reducing comparability between multiple experiments. Therefore, we aimed to build an easy-to-use computational tool for the processing of CLIP data that can be used for both iCLIP and eCLIP data, as well as data from other truncation-based CLIP methods.
Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.
racoon_clip is implemented as a Snakemake-powered command line tool (Snakemake version ≥7.22, Python version ≥3.9). The latest release can be downloaded from GitHub (https://github.com/ZarnackGroup/racoon_clip/tree/main) and installed via pip. A detailed documentation, including installation, usage, and customization, can be found at https://racoon-clip.readthedocs.io/en/latest/. The example datasets can be downloaded from the Short Read Archive (SRA; iCLIP: SRR5646576, SRR5646577, SRR5646578) or the ENCODE Project (eCLIP: ENCSR202BFN).
与RNA结合蛋白相关的大量生物学问题都可以通过紫外光交联免疫沉淀(CLIP)实验来解决。然而,CLIP数据的处理和分析相当复杂。此外,不同类型的CLIP实验,如iCLIP或eCLIP,通常采用不同的处理方式,这降低了多个实验之间的可比性。因此,我们旨在构建一个易于使用的计算工具来处理CLIP数据,该工具可用于iCLIP和eCLIP数据,以及来自其他基于截短的CLIP方法的数据。
在这里,我们介绍了racoon_clip,这是一个可持续且完全自动化的流程管道,可以对iCLIP和eCLIP数据进行完整处理,以单核苷酸分辨率提取RNA结合信号。racoon_clip易于安装和执行,具有多个预设和完全可定制的参数,并输出一份结论性的总结报告,其中包含所有分析步骤的可视化结果和统计数据。
racoon_clip被实现为一个由Snakemake驱动的命令行工具(Snakemake版本≥7.22,Python版本≥3.9)。最新版本可从GitHub(https://github.com/ZarnackGroup/racoon_clip/tree/main)下载,并通过pip进行安装。详细的文档,包括安装、使用和定制说明,可在https://racoon-clip.readthedocs.io/en/latest/上找到。示例数据集可从短读存档库(SRA;iCLIP:SRR5646576、SRR5646577、SRR5646578)或ENCODE项目(eCLIP:ENCSR202BFN)下载。